Heart rate monitoring and estimation is essential parameter in biomedical engineering and medicine. The heartbeat rate change would affect directly to the physiological/ pathological state (mood, stress, behaviour) of a person. The estimation of heart rate is an important factor to determine the pathological and physiological state of a person/individual.
Papers:
S. Kazemi, A. Ghorbani, H. Amindavar, and C. Li, “Cyclostationary approach to Doppler radar heart and respiration rates monitoring with body motion cancelation using Radar Doppler System,” Biomed. Signal Process. Control, vol. 13, pp. 79–88, Sep. 2014.
D. J. McDuff, J. R. Estepp, A. M. Piasecki, and E. B. Blackford, “A survey of remote optical photoplethysmographic imaging methods,” in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015, pp. 6398–6404
Hi Eduard,
there are many works in the field, but to date the usage of CNN or invastigations on it are not really common. An obvious way would be to use them for detection and tracking. Here is one work which makes use of CNN:
https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10501/1050112/Data-fusion-for-improved-camera-based-detection-of-respiration-in/10.1117/12.2290139.full
Greetings, Sebastian
Dear Christian Pilz
, Eduard Babulak and Sebastian Zaunseder,I agree that claiming HR results on heavily compressed MAHNOB or COHFACE databases does not make sense. We did some compression experiments in: "Spetlik, R., Cech, J., Matas, J.: Non-Contact Reflectance Photoplethysmography: Progress, Limitations, and Myths" https://ieeexplore.ieee.org/document/8373904
In that paper, we also comment on the taxonomy of non-contact reflectance PPG methods, so what is meant by the rPPG, iPPG, and other abbreviations really depends on the author :)
We also created a publicly available dataset with uncompressed 4:2:0 videos with ECG ground truth - checkout http://cmp.felk.cvut.cz/~spetlrad/ecg-fitness/
Best regards...
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